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arXiv · 1102.2857

The Capra Research Program for Modelling Extreme Mass Ratio Inspirals

Abstract

Suppose a small compact object (black hole or neutron star) of mass $m$ orbits a large black hole of mass $M \gg m$. This system emits gravitational waves (GWs) that have a radiation-reaction effect on the particle's motion. EMRIs (extreme--mass-ratio inspirals) of this type will be important GW sources for LISA; LISA's data analysis will require highly accurate EMRI GW templates. In this article I outline the "Capra" research program to try to model EMRIs and calculate their GWs \textit{ab initio}, assuming only that $m \ll M$ and that the Einstein equations hold. Here we treat the EMRI spacetime as a perturbation of the large black hole's "background" (Schwarzschild or Kerr) spacetime and use the methods of black-hole perturbation theory, expanding in the small parameter $m/M$. The small body's motion can be described either as the result of a radiation-reaction "self-force" acting in the background spacetime or as geodesic motion in a perturbed spacetime. Several different lines of reasoning lead to the (same) basic $\O(m/M)$ "MiSaTaQuWa" equations of motion for the particle. Surprisingly, for a nonlinear field theory such as general relativity, modelling the small body as a point particle works well. The particle's own field is singular along the particle worldline so it's difficult to formulate a meaningful "perturbation" theory or equations of motion there. I discuss "mode-sum" and "puncture-function" regularization schemes that resolve this difficulty and allow practical self-force calculations, and I outline an important recent calculation of this type. Most Capra research to date has used 1st order perturbation theory. To obtain the very high accuracies needed to fully exploit LISA's observations of the strongest EMRIs, 2nd order perturbation theory will probably be needed.

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Jonathan Thornburg. 2011-02-14. The Capra Research Program for Modelling Extreme Mass Ratio Inspirals. https://arxiv.org/abs/1102.2857

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